Dataset of heatwave exposure caused by UHI

We constructed a dataset to assess the exposure of urban human settlements to heat waves caused by urban heat islands worldwide from 2003 to 2020. This dataset uses an adaptive urban-rural threshold method to determine the impact range of urban heat islands, and uses the spatially and temporally fitted MODIS surface temperature dataset to solve the problem of data loss caused by cloud pollution, achieving quantification of heat wave exposure in global urban human settlements caused by urban heat islands at a resolution of 1km. We provide relevant heat wave exposure data in the form of quantitative datasets, which can clearly deconstruct the contributions of background climate, local landscape, and urbanization effects to heat wave exposure. This provides a scientific basis for clarifying key mitigation areas of urban heat islands and developing heat wave risk warning models that consider the impact of urban heat islands. Our method and dataset provide support for collaborative decision-making on urban climate adaptation and sustainable development, and its technical framework can be extended to research on urban heat islands and heat wave exposure in other regions around the world本研究构建了一套2003—2020年全球尺度的数据集，用于评估全球城市人居环境受城市热岛效应引发的热浪暴露水平。本数据集采用自适应城乡阈值法确定城市热岛效应的影响范围，并借助经时空拟合的MODIS（Moderate Resolution Imaging Spectroradiometer，中分辨率成像光谱仪）地表温度数据集，解决了云污染导致的数据缺失问题，实现了1km分辨率下全球城市人居环境受城市热岛效应引发的热浪暴露水平的量化评估。本研究以量化数据集形式发布相关热浪暴露数据，可清晰解构背景气候、局地景观及城市化效应对热浪暴露水平的贡献份额。该成果可为明确城市热岛效应重点治理区域、构建考虑热岛效应影响的热浪风险预警模型提供科学依据。本研究的方法与数据集可为城市气候适应与可持续发展的协同决策提供支撑，其技术框架亦可推广至全球其他区域的城市热岛效应及热浪暴露相关研究。